Geometric rectification improves the horizontal positional accuracy of the imagery by warping the imagery to match the client's vectors or accurate ground control, and is suitable where the area is largely flat and the imagery has been acquired from nadir (near vertical) viewing. For areas where there is undulating topography, or the imagery has been acquired at a high angle to the vertical, or very high accuracy is required, orthorectification is necessary. Orthorectification is basically rectification that incorporates a digital elevation model (DEM) to compensate for topographic relief by allowing the vertical aspect to also be taken into account. GEOIMAGE uses PCI OrthoEngine which has specific satellite sensor math models to generate very precise orthoimages. Orthorectification is also usually required if several images or scenes need to be mosaicked in order to ensure that the joins are seamless. For both rectification and orthorectification, accurate ground control is essential to produce geometrically accurate imagery.

Pan-Sharpening

Most of the VHR and medium resolution satellites now capture data in one high resolution panchromatic band and several lower resolution multispectral bands where the pixel size of the multispectral data is a multiple of the pixel size of the pan band. GEOIMAGE has perfected the technique of merging such datasets to produce a colour image showing the better detail of the panchromatic image. The client therefore receives a colour image, which is better suited to a range of applications, such as vegetation mapping, or simply as a backdrop to vectors, with the higher spatial resolution allowing the client to see more detail.

In most instances, the pan/multi imagery is captured simultaneously and is co-registered and the imagery can be pan-sharpened or merged without prior orthorectification.

In cases where imagery from different satellites are to be pansharpened, such as merging the 25m multispectral Landsat5 imagery with 10m AVNIR-2 imagery, the images first need to be orthorectified to ensure that they exactly co-register with each other. GEOIMAGE will recommend which datasets can be pan-sharpened to ensure you get the best spatial and spectral resolution possible.

Deglinting

VHR satellite imagery over aquatic areas often exhibit water-surface-reflected sunlight along the slopes or crests of waves generated by surface winds. The effects of this “glint” can be enhanced by the collection of imagery at large off-nadir angles. Techniques involving the estimation of the glint using near infrared bands have been developed and can be applied to the data to enhance the information in the visible bands.

WorldView-2 multispectral image over Dingo Reef, Great Barrier Reef, Queensland. The image was captured on 05 December 2009 with an off-nadir angle of 18 degrees and obviously high surface wind conditions. The bands displayed are 5,3,2 in RGB and the left hand side is the raw data and the right hand side has been deglinted by Geoimage.

Image C - An overlapping image collected on 06 February 2010 at 20deg off nadir and wind speeds of 6 km/hr from the north-west. This image did not need deglinting and shows the same subsurface features.

Haze removal

Haze and smoke on images is a common problem in some areas of the world where the local farmers burn off after harvesting. The very high resolution operators do not consider that haze is sufficient to exclude the purchase of new capture imagery using the 15% cloud rule. Geoimage has developed techniques to lessen the impact of the haze in colour imagery.

Calibration

In remote sensing applications, the most common use of calibrated satellite data is to facilitate change detection of multi-temporal images. Geoimage routinely carries out the processes involved in Landsat calibration which include:

Preparation of imagery to ensure “exact” co-registration of multi-temporal images.

Conversion of the digital numbers in a raw image back to radiance, a measurable physical quantity using a simple gain and offset calculation for each band.

Correction of the Bi-Directional Reflectance Distribution Function (BRDF) effect which is due to surface reflectance characteristics that vary with the position of the image (latitude) and the elevation and azimuth of both the satellite and the sun.

Regression of known invariant targets against the standard or base.

In an accurately co-registered and calibrated image any changes between the calibrated scene and the standard can be attributed to natural variation.

Where the end use of the calibrated imagery is to measure vegetation differences, atmospheric effects (aerosols, haze, water vapour) are typically ignored.

Where satellite imagery is to be used in ocean studies and atmospheric effects interfere with the analyisis , atmospheric models or approximations are used to calibrate the imagery. Geoimage have successfully implemented an approximation approach to correcting 8-band Worldview 2 data for use in bathymetric studies.